dist_gcms {chooseGCM} | R Documentation |
Distance Between GCMs
Description
This function compares future climate projections from multiple General Circulation Models (GCMs) based on their similarity in terms of variables. It calculates distance metrics and plots the results on a heatmap.
Usage
dist_gcms(
s,
var_names = c("bio_1", "bio_12"),
study_area = NULL,
scale = TRUE,
method = "euclidean"
)
Arguments
s |
A list of stacks of General Circulation Models (GCMs). |
var_names |
Character. A vector of names of the variables to compare, or 'all' to include all variables. |
study_area |
An Extent object, or any object from which an Extent object can be extracted. Defines the study area for cropping and masking the rasters. |
scale |
Logical. Whether to apply centering and scaling to the data. Default is |
method |
Character. The correlation method to use. Default is "euclidean". Possible values are: "euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski", "pearson", "spearman", or "kendall". |
Value
A list containing two items: distances
(the calculated distances between GCMs) and heatmap
(a plot displaying the heatmap).
Author(s)
Luíz Fernando Esser (luizesser@gmail.com) https://luizfesser.wordpress.com
See Also
Examples
var_names <- c("bio_1", "bio_12")
s <- import_gcms(system.file("extdata", package = "chooseGCM"), var_names = var_names)
study_area <- terra::ext(c(-80, -30, -50, 10)) |> terra::vect(crs="epsg:4326")
dist_gcms(s, var_names, study_area, method = "euclidean")